Analytics

Best 13 Free Financial Datasets for Machine Learning [Updated]

Financial services companies are leveraging data and machine learning to mitigate risks like fraud and cyber threats and to provide a modern customer experience. By following these measures, they are able to comply with regulations, optimize their trading and answer their customers’ needs. In today’s competitive digital world, these changes are essential for ensuring their relevance and efficiency.

How to use GenAI for database query optimization and natural language analysis

In the past, querying a database required Structured Query Language (SQL) skills, or knowledge of other database query languages, such as Kibana Query Language (KQL). Today, with the emergence of generative AI (GenAI), teams can query their analytic database using natural language — and get plain English results in return. Or, if you prefer to still use SQL, many teams use GenAI for database query optimization, making queries faster and more efficient.

Continual is SOC 2 compliant

Continual is proud to announce that we are now SOC 2 Type 1 compliant and SOC 2 Type 2 in progress. This certification demonstrates our core commitment to your data security and privacy. We expect to make additional announcements around our security certification efforts over the coming months. Beyond third party attestations, Continual is built from the ground up for data security, privacy, and governance at enterprise scale.

Introduction to Ozone on Cloudera Data Platform

When considering whether Ozone is the right fit for your company, view it from several different angles. You can look at it from the perspective of Lower TCO, or reducing the carbon footprint of your Data Center. Other things to consider are how much your data is increasing and at what rate, and if you have enough hardware to cover that growth.

Navigating XML Import Errors: A Guide for Data Professionals

In the realm of data engineering, XML (Extensible Markup Language) plays a pivotal role in the exchange and storage of structured data. Its flexibility and widespread acceptance make it a cornerstone for data interchange across diverse systems. However, the process is not without its hurdles. XML import errors can pose significant challenges, impacting data integrity and workflow efficiency.

What is the Event Sourcing Pattern? | Designing Event-Driven Microservices

Event Sourcing is a pattern of storing an object's state as a series of events. Each time the object is updated a new event is written to an append-only log. When the object is loaded from the database, the events are replayed in order, reapplying the necessary changes. The benefit of this approach is that it stores a full history of the object. This can be valuable for debugging, auditing, building new models, and a variety of other situations. It is also a technique that can be used to solve the dual-write problem when working with event-driven architectures.

Complete Guide to Database Schema Design

Experts predict that the global enterprise data management market will grow at a compound annual growth rate of 12.1% until 2030. Your organization’s database management system (DBMS) stores all the enterprise data you need for software applications, systems, and IT environments, helping you make smarter data-driven business decisions. Here are the key things to know about database schema design.